Understanding the Expenditure and Recovery of Anaerobic Work Capacity Using Noninvasive Sensors

The objective of this research is to advance the understanding of human performance to allow for optimized efforts on specific tasks. This is accomplished by 1) understanding the expenditure and recovery of Anaerobic Work Capacity (AWC) as related to the Critical Power (CP) of a human, and 2) determining if and how a case for an energy-management system to optimize energy expenditure and recovery can be made in real-time using noninvasive sensors. As humans exert energy, the body converts fuel into mechanical power through both aerobic and anaerobic energy systems. The mechanical power produced can be measured through the use of a cycle ergometer and the use of the energy systems can be measured by observing biological artifacts with sensors. There is a Critical Power level that a human can theoretically operate at indefinitely and there is a well-established theory in the literature to predict the depletion of a human’s finite Anaerobic Work Capacity based on this Critical Power. The literature however lacks a robust model for understanding the recovery of the Anaerobic Work Capacity. Because of this, a cycling study was conducted with ten regularly-exercising subjects (9 male, 1 female aged 23-44). First, the CP and AWC of the subjects were determined by a 3-minute all-out intensity cycling test. The subjects performed several interval protocols to exhaustion with recovery intervals to quantify how much AWC was recovered in each interval. Results: It was determined that sub-Critical Power recovery is not proportional to above-Critical Power expenditure. The amount of AWC recovered is influenced more by the power level held during recovery than the amount of time spent in recovery. The following conclusions are discussed in this thesis: 1) relationships between measurable biological artifacts and biological processes that are proven to exist in the literature; 2) expenditure and recovery of Anaerobic Work Capacity; 3) methods to use real-time, noninvasive sensor data to determine the status of human work capacity; and 4) how the results can be used in a human-in-the-loop feedback control system to optimize performance for a given task

Modeling the Expenditure and Recovery of Anaerobic Work Capacity in Cycling

The objective of this research is to model the expenditure and recovery of Anaerobic Work Capacity (AWC) as related to Critical Power (CP) during cycling. CP is a theoretical value at which a human can operate indefinitely and AWC is the energy that can be expended above CP. There are several models to predict AWC-depletion, however, only a few to model AWC recovery. A cycling study was conducted with nine recreationally active subjects. CP and AWC were determined by a 3-min all-out test. The subjects performed interval tests at three recovery intervals (15 s, 30 s, or 60 s) and three recovery powers (0.50CP, 0.75CP, and CP). It was determined that the rate of expenditure exceeds recovery and the amount of AWC recovered is influenced more by recovery power level than recovery duration. Moreover, recovery rate varies by individual and thus, a robust mathematical model for expenditure and recovery of AWC is needed

Modeling the Expenditure and Recovery of Anaerobic Work Capacity in Cycling

The objective of this research is to model the expenditure and recovery of Anaerobic Work Capacity (AWC) as related to Critical Power (CP) during cycling. CP is a theoretical value at which a human can operate indefinitely and AWC is the energy that can be expended above CP. There are several models to predict AWC-depletion, however, only a few to model AWC recovery. A cycling study was conducted with nine recreationally active subjects. CP and AWC were determined by a 3-min all-out test. The subjects performed interval tests at three recovery intervals (15 s, 30 s, or 60 s) and three recovery powers (0.50CP, 0.75CP, and CP). It was determined that the rate of expenditure exceeds recovery and the amount of AWC recovered is influenced more by recovery power level than recovery duration. Moreover, recovery rate varies by individual and thus, a robust mathematical model for expenditure and recovery of AWC is needed